Simulation of peak-demand hydrographs in pressurized irrigation delivery systems using a deterministic–stochastic combined model. Part II: model applications

A deterministic–stochastic combined model named HydroGEN was developed, as described in a companion paper (Part I: Model development), to enable the simulation of demanded daily volumes and hourly flow rates during peak periods in pressurized irrigation delivery networks. The model was applied to a pilot large-scale irrigation system located in southern Italy for calibration and for testing its reliability in analyzing the operation of large-scale pressurized delivery systems through the simulated flow configurations. Daily input data on rainfall, temperature, solar radiation, wind speed and relative humidity were gathered from a meteorological station located within the study area, whereas information on local irrigation management practices were collected through interviews with farmers and from extension specialists. The model was tested at different management levels, from district to sector and hydrants. The model testing was supported by the use of high-resolution remote-sensing imagery acquired on a single overpass date in 2006 and then classified and recoded following a ground-truthing campaign conducted during the same year. Simulations were performed to identify the 10-day peak-demand period and to generate the hydrographs of daily volumes and of hourly flow rates. Results from the different simulations were compared with historical datasets of irrigation volumes and discharges recorded during the 2008 and 2009 seasons at the upstream end of the irrigation network under study, at a sector level during the 2007 season and at selected delivery hydrants during the 2005 season. Some discrepancies between simulated and recorded data were noted that can be related to small errors in estimating crop and soil parameters, application efficiency at field level, as well as to large variability in irrigation management practices followed by local farmers. Overall, the results from testing showed that the model is capable of forecasting with good accuracy the timing of peak-demand periods, the irrigation volumes demanded during the season, as well as the hydrographs of daily volumes and hourly flow rates withdrawn by farmers during these peak-demand periods, especially when it is applied to large multi-cropped command areas.     

Soil apparent electrical conductivity and must carbon isotope ratio provide indication of plant water status in wine grape vineyards

Precision Agriculture - Proximal sensing is being integrated into vineyard management as it provides rapid assessments of spatial variability of soils’ and plants’ features. The...     

Modeling delivery performance in pressurized irrigation systems from simulated peak-demand flow configurations

A methodology to assess performance of pressurized irrigation distribution networks is presented, which is based on generation of flow configurations from simulated delivery scenarios, and on subsequent analysis of network operation and delivery achievements. The rationale of the methodology entails simulating the peak-demand flow configurations in the pipe network through a deterministic–stochastic combined agro-hydrological model, and forecasting the delivery performance by means of a hydraulic simulation model and of some specific performance indicators. The agro-hydrological model generates disaggregated information on soil water deficits for all the cropped fields downstream from the delivery hydrants, and forecasts the demand flow hydrographs and irrigation deliveries for the entire service area during peak-demand periods. The simulated-demand flow configurations are then passed on to the hydraulic simulation model, which evaluates the hydraulic performance achievable by the pipe network. The performance analysis is then refined using additional indicators specifically adapted to pressurized irrigation networks. The proposed methodology was applied to a large-scale pressurized irrigation system of southern Italy that is in need of modernization. Results proved the usefulness of the combined use of simulation tools as components of an analytical framework to address modernization and re-engineering of existing irrigation delivery networks, on the basis of targeted delivery performance.     

Flexible delivery schedules to improve farm irrigation and reduce pressure on groundwater: a case study in southern Italy

This study was conducted on an irrigated area of southern Italy to analyze the current operation of a large-scale irrigation delivery system and the effects of the operation procedures on crop irrigation management and aquifer salinity increase. The area is characterized by relatively high levels of groundwater salinity in the summer that are probably due to intensive groundwater pumping by farmers during periods of peak irrigation demand, with the resulting seawater intrusion. Two alternative delivery schedules, namely the rotation delivery schedule and the flexible delivery schedule, referred to as RDS and FDS, respectively, were simulated using a soil-water balance model under different combinations of crop, soil and climatic conditions. The first set of simulations concerned the farm irrigation management constrained by the rotational delivery used by the local water management organization. The second scenario simulated the farm irrigation schedule most commonly used by growers in the area for maximizing crop yields. Based on crop irrigation management under RDS and FDS, two alternative operational scenarios were also developed at the scheme level and then compared for evaluation. Winter and summer salinity maps of the aquifer were developed by interpolating salinity measurements of the groundwater samples collected during the 2006 irrigation season. From these maps, a close relationship can be inferred among delivery schedule, aquifer exploitation and salinity increase, which justifies the need for implementing FDS that might reduce the groundwater demand for irrigation.     

Simulation of peak-demand hydrographs in pressurized irrigation delivery systems using a deterministic–stochastic combined model. Part I: model development

This study describes a model named HydroGEN that was conceived for simulating hydrographs of daily volumes and hourly flow rates during peak-demand periods in pressurized irrigation delivery networks with on-demand operation. The model is based on a methodology consisting of deterministic and stochastic components and is composed of a set of input parameters to reproduce the crop irrigation management practices followed by farmers and of computational procedures enabling to simulate the soil water balance and the irrigation events for all cropped fields supplied by each delivery hydrant in a distribution network. The input data include values of weather, crop, and soil parameters, as well as information on irrigation practices followed by local farmers. The resulting model outputs are generated flow hydrographs during the peak-demand period, which allow the subsequent analysis of performance achievable under different delivery scenarios. The model can be applied either for system design or re-design, as well as for analysis of operation and evaluation of performance achievements of on-demand pressurized irrigation delivery networks. Results from application of HydroGEN to a real pressurized irrigation system at different scales are presented in a companion paper (Part II: model applications).